Statistics in Medicine: Edition 2

Robert H. Riffenburgh

2011年8月 · Elsevier

關於本電子書

Medicine deals with treatments that work often but not always, so treatment success must be based on probability. Statistical methods lift medical research from the anecdotal to measured levels of probability. This book presents the common statistical methods used in 90% of medical research, along with the underlying basics, in two parts: a textbook section for use by students in health care training programs, e.g., medical schools or residency training, and a reference section for use by practicing clinicians in reading medical literature and performing their own research. The book does not require a significant level of mathematical knowledge and couches the methods in multiple examples drawn from clinical medicine, giving it applicable context.

• Easy-to-follow format incorporates medical examples, step-by-step methods, and check yourself exercises
• Two-part design features course material and a professional reference section
• Chapter summaries provide a review of formulas, method algorithms, and check lists
• Companion site links to statistical databases that can be downloaded and used to perform the exercises from the book and practice statistical methods

New in this Edition:

• New chapters on: multifactor tests on means of continuous data, equivalence testing, and advanced methods
• New topics include: trial randomization, treatment ethics in medical research, imputation of missing data, and making evidence-based medical decisions
• Updated database coverage and additional exercises
• Expanded coverage of numbers needed to treat and to benefit, and regression analysis including stepwise regression and Cox regression
• Thorough discussion on required sample size

關於作者

Robert H. Riffenburgh, PhD, advises on experimental design, statistical analysis, and scientific integrity of the approximately 400 concurrent studies at the Naval Medical Center San Diego. A fellow of the American Statistical Association and Royal Statistical Society, he is former Professor and Head, Statistics Department, University of Connecticut, and has been faculty at Virginia Tech., University of Hawaii, University of Maryland, University of California San Diego, San Diego State University, and University of Leiden (The Netherlands). He has been president of his own consulting firm and performed and directed operations research for the U.S. government and for NATO. He has consulted on biostatistics throughout his career, has received numerous awards, and has published more than 140 professional articles.